Lately, I’ve been focusing on attaining more discipline in my professional life as a startup founder. It had become apparent to me that I needed to step up and make it happen. Striving for it has raised an interesting question in my mind — could positive thinking be delusional at times, and consequently counter-productive?

You see, a positive mindset can often lead to a mirage, a state of daydreaming that fools us into believing that we are self-aware and in complete control. Most people have to confront sloth, as I did too, due to the comfort zone nested by immoderate hopefulness.

For centuries cognition has tricked on humans into believing their actions are completely thought-out and preplanned. Modern psychology says otherwise. Much of human behaviour is still rooted and influenced by our “old brain,” the part of our mind controlling the survival instincts that kept our ancestors alive. This subconscious stimulus (optimism bias, updated 9 Oct) keeps us going, but the downside is that hopefulness can very easily make us less determined. Laziness can give way to lack of focus and procrastination, and before we realize it our positive thoughts would silently slide plans into dormancy.

A recent opinion piece in the New York Times also reflected on this phenomenon:

What if all this positivity is part of the problem? What if we’re trying too hard to think positive and might do better to reconsider our relationship to “negative” emotions and situations?

..visualizing a successful outcome, under certain conditions, can make people less likely to achieve it.

Ancient philosophers and spiritual teachers understood the need to balance the positive with the negative, optimism with pessimism, a striving for success and security with an openness to failure and uncertainty. The Stoics recommended “the premeditation of evils,” or deliberately visualizing the worst-case scenario. This tends to reduce anxiety about the future: when you soberly picture how badly things could go in reality, you usually conclude that you could cope. Besides, they noted, imagining that you might lose the relationships and possessions you currently enjoy increases your gratitude for having them now. Positive thinking, by contrast, always leans into the future, ignoring present pleasures.

Positive affirmation should be more like an expression of joy and less like a stressful effort to stamp out any trace of negativity, the article expresses rightfully. It’s a valid measure, which should apply to our work (workplaces) as much as it applies to our lives. Many businesses, particularly the bigger ones, ruthlessly reinforce optimism with beliefs like “stay upbeat at all times” or “quick wins for big growth”, more so at times of a slow-down or recession. The prevailing financial crisis in many ways is an outcome of such over-optimism, as one other article speculates:

No one was psychologically prepared for hard times when they hit, because, according to the tenets of positive thinking, even to think of trouble is to bring it on.

A common pitfall occurs when people automatically connect positive thinking with happiness, writes a people-management thinker:

And so it is in the workplace, where positive employees are lauded and the negative are derided. Positive employees are seen as team players but negative workers are condemned as outcasts. The consequence is that realistic and rational people, usually the negative thinkers, remain unheard.

You see this happening in the way Human Resources departments reframe language to make it sound more positive. ‘Negative feedback’ has become ‘areas for improvement’. A ‘demotion’ has become ‘a new opportunity’. ‘Problems’ have become ‘challenges’.

So if optimism is as myopic and hazardous for us as pessimism and if neither is superior, then what could be a more effective mindset?

Maybe realism is one such alternative — the ability to be prepared for the worst, but still believe for the best to occur. Just like many successful businesses, people can rationally get it right by setting practically high goals, putting contingency plans in place and having gratitude for everything that creates (a sense of) abundance in their life & work.

Even my 4 year old daughter is wise to learn that “you get what you get, you don’t get upset.” As for her wishful thinking to feast on dessert each night, she is learning to be thankful for having that privilege and also to stay prepared for not receiving it each night.

When 1 in 3 humans are affected by a disease, it needs attention and help from all corners. There are many types of cancers, so it’s hard to say if we’ll ever be able to completely cure cancer. But prevention, early detection and proper care are crucial in cancer diagnosis and its treatment.

In health care today, we spend most of the dollars — in terms of treating disease — in the last two years of a person’s life.

I pondered on it one evening and thought I’d find out about some “programmable” possibilities related to cancer research for hackers from the non-scientific community, besides the obvious means of help like donations (both charity and research), awareness drives and volunteering.

I got in touch with Jon Kiddy, a software engineer who works at Roswell Park Cancer Institute. Jon kindly shared his views and pointed out that the current state of cancer research can be summed up in one of Daniel Markham’s excellent posts. After having read the book on the subject called “The Emperor of All Maladies”, Daniel went on to state the general problem with cancer research is that the US healthcare isn’t setup to support individualized care and treatment, which is currently undergoing the most intensive scrutiny. A commentor on Hacker News responded to Daniel’s post with this inspiring message:

You want to fix cancer, don’t wait for the scientists. They are hobbled by regulation. Be an engineer: get out there and make one of the viable solutions work, and make it work outside the US.

What started as modest self-education, has led me to several impactful ways in helping with cancer research:

1. Distributed Computing Projects – In 2003, with grid computing, in less than three months scientists identified 44 potential treatments to fight the deadly smallpox disease. Without the grid, the work would have taken more than one year to complete. Participating in a distributed computing project is the easiest way to get involved with cancer research.

Grid computing works by splitting complex computations into small pieces that can be processed simultaneously on individual public nodes, there-by reducing research time and making the technology infrastructure cost-effective.

2. Build on “Big Data” – Massive amounts of raw data is available for analysis in cancer research. As Jon wrote back to me:

The problem comes when there is such a large amount of data to process in a field where each individual’s treatment is usually uniquely suited only to them. Hadoop/Hbase is in use by The Cancer Genome Atlas to make some of this process more bearable. Their datasets are invaluable.

The combination of Apache Hadoop (for distributed computing), HBase (distributed database), MapReduce (for distributed computing on large datasets on clusters of computers), R Project (for statistical computing), and Gephi (for visualization and exploration) changes the way we think about analysis of Big Data.

Data analysis, data visualization and even Web crawler technology are all important in cancer research, for processing highly distributable problems across huge datasets using a large number of computers.

Instead of focusing on a handful of outcomes, we can process all of the events in the data set at the same time. We can try out hundreds of different strategies for cleaning records, stratifying observations into clusters, and scoring drug-reaction tuples, run everything in parallel, and analyze the data at a fraction of the cost of a traditional supercomputer. We can render the results of our analyses using visualization tools that can be used by domain experts to explore relationships within our data that they might never have thought to look for. By dramatically reducing the costs of exploration and experimentation, we foster an environment that enables innovation and discovery.

3. Apps and Tools – Personal profiling and monitoring could be another area of focus for developers interested in cancer research or general health-related diagnosis.

or a Web-based tool (similar to mappiness or TrackYourHappiness) to monitor a persons diet (it’s been widely discussed that smoking, ingestion of sugar and excessive red meat may set the stage for rise in cancer occurrences).

There are lots of possibilities for personal solutions that aid in collective science.

“In lieu of spending a decade in training to become an oncologist, I have been able to put my skills to practical use.”, Jon says about the impact he’s making.

I really wish for many more technology enthusiasts to devote their time, skills and efforts in the fight against cancer. In what other ways can we help? Do share your comments and views.

Why work on problems few care much about and no one will pay for, when you could fix one of the most important components of the world’s infrastructure? Because schlep blindness prevented people from even considering the [difficult] idea of fixing payments [that Stripe is doing].

I completely agree with Paul. However, I also tend to think that there’s a reverse schlep blindness at play in a lot of cases. Some startup founders often subconsciously ignore or avoid problems that seem too simple to solve. They would rather work on complex problems, requiring complicated architectures, plethora of ‘cool’ technologies and ‘beautifully’ intricate code, all of which few care much about and no one will pay for. Maybe it’s another form of schlep, a cognitive bias after all.

‘Too simple to do’ doesn’t mean that it’s easy to build, easy to sell and unfeasible as a business because one might think there aren’t any paying customers for it. Such markets are often overlooked and eventually existing competition suffers a slow death due to lack of innovation and new ideas.

Hard problems are good, because both good and bad solutions to those tedious problems will result in learning, eventual innovation and disruption. Simple problems are good too, because their execution will require a radical (yet simple) solution, and that’s hard to do in itself.